In fact, the essential principle of deterministic mapping among different channels is that users at different spaces or different frequencies experience the same electromagnetic environment. Utilizing such deterministic mapping, the CSI at one space/frequency point can be used to predict the CSI at another space/frequency point, which is referred to as \(\mathrm {\it channel~extrapolation}\) .
Clearly, channel extrapolation can be excitingly useful to reduce the training cost over massive MIMO related systems.
Inspired by the universal approximation capability of deep learning (DL) [1]}, [2]}, [3]}, it is possible to use DL to characterize the mapping among channels at different space/frequency locations.
